JSM 2004 - Toronto

Abstract #301849

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Activity Number: 413
Type: Contributed
Date/Time: Thursday, August 12, 2004 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #301849
Title: Estimating Conditional Survival Probability with Cox's PH Model for Two-stage Design Studies
Author(s): Gang Li*+ and Chi-hong Tseng
Companies: University of California, Los Angeles and University of California, Los Angeles
Address: Dept. of Biostatistics, Los Angeles, CA, 90095-1772,
Keywords: survival data ; two-stage design
Abstract:

We present a method to estimate the conditional survival probability for a two-stage design study under the framework of Cox's Proportional Hazard Model. A typical setting involoves a first-stage sample drawn from population of interest and a second-stage sample, which is a subsample of the first-stage sample. The first-stage sample usually contains cheaper, rough, or incomplete information, while the second-stage sample consists of accurate and complete information. Our proposed method combines both datasets to estimate the conditional probability and achieve higer asymptotic efficency than estimation based only on the second-stage sample. A simulation study is presented to illustrate the effectiveness of this method and applications to the SEER dataset on cancer incidence and survival are discussed.

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